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Morphology plays a crucial role in defining the optical, electronic, and mechanical properties of halide perovskite microcrystals. Therefore, developing strategies that offer precise control over crystal morphology during the growth process is highly desirable. This work presents a simple scheme to simultaneously grow distinct geometries of cesium lead bromide (CsPbBr3) microcrystals, including microrods (MR), microplates (MP), and microspheres (MS), in a single chemical vapor deposition (CVD) experiment. By strategically adjusting precursor evaporation temperatures, flux density, and the substrate temperature, we surpass previous techniques by achieving simultaneous yet selective growth of multiple CsPbBr3 geometries at distinct positions on the same substrate. This fine growth control is attributed to the synergistic variation in fluid flow dynamics, precursor substrate distance, and temperature across the substrate, offering regions suitable for the growth of different morphologies. Pertinently, perovskite MR are grown at the top, while MP and MS are observed at the center and bottom regions of the substrate, respectively. Structural analysis reveals high crystallinity and an orthorhombic phase of the as-grown perovskite microcrystals, while persistent photonic lasing manifests their nonlinear optical characteristics, underpinning their potential application for next-generation photonic and optoelectronic devices. [ABSTRACT FROM AUTHOR]

The desert locust, Schistocerca gregaria (Forsk., 1775), stands as one of the most pervasive pests globally, inflicting extensive damage across Asia and Africa. Facilitated by intercontinental migration, the desert locust engages in population exchange between different source areas, perpetuating its widespread proliferation. Despite the wind being recognized as a key factor during migration events, elucidating its precise influence on intercontinental migration has remained elusive. In this study, we scrutinized monitoring data sourced from the FAO monitoring system, pinpointing 13 desert locust events featuring intercontinental migrations since 1967. From these events, four migration routes were summarized, traversing the Red Sea (RS-WE and RS-EW) and the northern Indian Ocean (IO-WE and IO-EW). Typically, RS-WE and IO-EW migrations occurred between December and March, whereas RS-EW and IO-WE migrations were observed from May to June and April to July, respectively. Our examination of wind field data spanning the past 15 years revealed that wind direction and speed facilitated intercontinental migrations. Furthermore, migration trajectory modeling indicated that desert locusts might exhibit migratory behavior both during the day and at night in the cases of RS-WE and RS-EW, with cross-oceanic migration potentially lasting for a week for IO-WE and IO-EW. In summary, our study identifies four migration routes for the intercontinental migration of the desert locust, providing crucial support for the scientific prediction of its occurrence and contributing to international food security efforts. [ABSTRACT FROM AUTHOR]

Simple Summary: Aphis gossypii Glover is an economically important sap-sucking insect pest that causes severe damage worldwide. The flonicamid has been widely used for controlling sap-sucking insect pests, but its intergenerational sublethal effects on key demographic parameters of A. gossypii have not been fully studied. The age-stage, two-sex life table analysis was conducted to investigate the sublethal effects of flonicamid on the biological parameters of adult A. gossypii (F0) and its subsequent intergenerational effects on the offspring (F1 generation). The results showed that the sublethal concentrations of flonicamid significantly decreased the longevity, fecundity, and reproductive days of F0 A. gossypii. Moreover, flonicamid induced intergenerational sublethal effects on the subsequent progeny generation (F1) by impacting the key biological and demographic parameters of A. gossypii. Taken together, these results demonstrated that sublethal concentrations of flonicamid negatively affect the demographic parameters of A. gossypii, resulting in the suppression of population growth. Flonicamid is a novel systemic insecticide widely used against aphids. However, the intergenerational sublethal effects of flonicamid on cotton aphid, Aphis gossypii, have not been fully studied. This study aimed to evaluate the sublethal effects of flonicamid on the biological parameters of adult A. gossypii (F0) and its subsequent intergenerational effects on the offspring (F1 generation) through age-stage, two-sex life table analysis. The results of the bioassays indicate that flonicamid exhibits significant toxicity toward adult A. gossypii, as evidenced by an LC50 value of 0.372 mg L−1 after a 48-h exposure period. The longevity, fecundity, and reproductive days of adult cotton aphids (F0) were significantly decreased when treated with the sublethal concentrations of flonicamid. The pre-adult stage exhibited an increase, whereas the adult longevity, total longevity, and fecundity experienced a notable decrease in F1 aphids after the exposure of F0 aphids to sublethal concentrations of flonicamid. Furthermore, the key demographic parameters, including r, λ, R0, and RPd, showed a significant decrease, while the total pre-reproductive period (TPRP) experienced a significant increase in the F1 generation. Collectively, our findings indicate that sublethal concentrations of flonicamid impact the demographic parameters of A. gossypii, resulting in suppression of population growth. This study presents comprehensive information on the overall impact of flonicamid on A. gossypii, which could potentially aid in managing this major pest. [ABSTRACT FROM AUTHOR]

The cooperative, connected, and automated mobility (CCAM) infrastructure plays a key role in understanding and enhancing the environmental perception of autonomous vehicles (AVs) driving in complex urban settings. However, the deployment of CCAM infrastructure necessitates the efficient selection of the computational processing layer and deployment of machine learning (ML) and deep learning (DL) models to achieve greater performance of AVs in complex urban environments. In this paper, we propose a computational framework and analyze the effectiveness of a custom-trained DL model (YOLOv8) when deployed in diverse devices and settings at the vehicle-edge-cloud-layered architecture. Our main focus is to understand the interplay and relationship between the DL model's accuracy and execution time during deployment at the layered framework. Therefore, we investigate the trade-offs between accuracy and time by the deployment process of the YOLOv8 model over each layer of the computational framework. We consider the CCAM infrastructures, i.e., sensory devices, computation, and communication at each layer. The findings reveal that the performance metrics results (e.g., 0.842 mAP@0.5) of deployed DL models remain consistent regardless of the device type across any layer of the framework. However, we observe that inference times for object detection tasks tend to decrease when the DL model is subjected to different environmental conditions. For instance, the Jetson AGX (non-GPU) outperforms the Raspberry Pi (non-GPU) by reducing inference time by 72%, whereas the Jetson AGX Xavier (GPU) outperforms the Jetson AGX ARMv8 (non-GPU) by reducing inference time by 90%. A complete average time comparison analysis for the transfer time, preprocess time, and total time of devices Apple M2 Max, Intel Xeon, Tesla T4, NVIDIA A100, Tesla V100, etc., is provided in the paper. Our findings direct the researchers and practitioners to select the most appropriate device type and environment for the deployment of DL models required for production. [ABSTRACT FROM AUTHOR]

Thiamethoxam, a second-generation neonicotinoid insecticide is widely used for controlling sap-sucking insect pests including Rhopalosiphum padi. The current study aimed to investigate the life-history parameters and feeding behavior of R. padi following treatments with sublethal concentrations of thiamethoxam. The lethal concentration 50 (LC50) value of thiamethoxam against adult R. padi was 11.458 mg L−1 after 48 h exposure. The sublethal concentrations of thiamethoxam (LC5 and LC10) significantly decreased the adult longevity, fecundity, and reproductive days in the directly exposed aphids (F0 generation). In the progeny R. padi (F1), the developmental durations and total prereproductive period (TPRP) were decreased while the adult longevity, fecundity, and reproductive days (RPd) were increased at both thiamethoxam concentrations. The demographic parameters including the net reproductive rate (R0), intrinsic rate of increase (r), and finite rate of increase (λ) were prolonged only at the LC5 of thiamethoxam. The EPG results indicated that the sublethal concentrations of thiamethoxam increases the total duration of non-probing (Np) while reducing the total duration of E2 in directly exposed aphids (F0). Interestingly, the E2 were significantly increased in the progeny generation (F1) descending from previously exposed parental aphids (F0). Overall, this study showed that thiamethoxam exhibited high toxicity against directly exposed individuals (F0), while inducing intergenerational hormetic effects on the progeny generation (F1) of R. padi. These findings provided crucial details about thiamethoxam-induced hormetic effects that might be useful in managing resurgences of this key pest. [ABSTRACT FROM AUTHOR]

The bird cherry-oat aphid, Rhopalosiphum padi (L.) (Hemiptera: Aphididae) is one of the most economically important pests of wheat crops worldwide. Thiamethoxam, bifenthrin, and flonicamid are extensively used insecticides for controlling this key pest. However, the indiscriminate use of chemical insecticides has led to the development of resistance in insects. In this study, we assessed the development of selection-induced resistance to bifenthrin, flonicamid, and thiamethoxam under controlled laboratory conditions. Additionally, we employed the age-stage, two-sex life table method to examine the fitness of R. padi. After ten generations of selection, bifenthrin-, flonicamid-, and thiamethoxam-resistant strains of R. padi were developed with resistance levels of 34.46, 31.97, and 26.46-fold, respectively. The life table analysis revealed a significant decrease in adult longevity and fecundity in these resistant strains compared to susceptible strain. Furthermore, the key demographic parameters such as net reproductive rate (R0) and reproductive days exhibited a significant reduction in all resistant strains, while the intrinsic rate of increase (r) and finite rate of increase (λ) were decreased only in resistant strains to bifenthrin and thiamethoxam. Taken together, these findings provide a comprehensive understanding of laboratory-induced insecticide resistance evolution and the associated fitness costs in R. padi. This knowledge could help to design resistance management strategies against this particular pest of wheat. [ABSTRACT FROM AUTHOR]

Ixodid ticks are responsible for the transmission of various intracellular bacteria, such as the Rickettsia species. Little Information is available about the genetic characterization and epidemiology of Rickettsia spp. The current study was designed to assess the tick species infesting various livestock hosts and the associated Rickettsia spp. in Pakistan. Ticks were collected from different livestock hosts (equids, cattle, buffaloes, sheep, goats, and camels); morphologically identified; and screened for the genetic characterization of Rickettsia spp. by the amplification of partial fragments of the gltA, ompA and ompB genes. Altogether, 707 ticks were collected from 373 infested hosts out of 575 observed hosts. The infested hosts comprised 105 cattle, 71 buffaloes, 70 sheep, 60 goats, 34 camels, and 33 equids. The overall occurrence of Rickettsia spp. was 7.6% (25/330) in the tested ticks. Rickettsia DNA was detected in Rhipicephalus haemaphysaloides (9/50, 18.0%), followed by Rhipicephalus turanicus (13/99, 13.1%), Haemaphysalis cornupunctata (1/18, 5.5%), and Rhipicephalus microplus (2/49, 4.1%); however, no rickettsial DNA was detected in Hyalomma anatolicum (71), Hyalomma dromedarii (35), and Haemaphysalis sulcata (8). Two Rickettsia agents were identified based on partial gltA, ompA, and ompB DNA sequences. The Rickettsia species detected in Rh. haemaphysaloides, Rh. turanicus, and Rh. microplus showed 99–100% identity with Rickettsia sp. and Candidatus Rickettsia shennongii, and in the phylogenetic trees clustered with the corresponding Rickettsia spp. The Rickettsia species detected in Rh. haemaphysaloides, Rh. turanicus, Rh. microplus, and Ha. cornupunctata showed 100% identity with R. massiliae, and in the phylogenetic trees it was clustered with the same species. Candidatus R. shennongii was characterized for the first time in Rh. haemaphysaloides, Rh. turanicus, and Rh. microplus. The presence of SFG Rickettsia spp., including the human pathogen R. massiliae, indicates a zoonotic risk in the study region, thus stressing the need for regular surveillance. [ABSTRACT FROM AUTHOR]

Biogenic nanoparticles are considered effective alternatives to chemical pesticides for the management of pathogenic plant diseases. This study was focused on the synthesis of stable silver nanoparticles (AgNPs) to control challenging plant pathogenic bacteria in vitro and in planta. We synthesized AgNPs by reacting different proportions of silver nitrate and aqueous extract of Hedera nepalensis. The physicochemical properties of the synthesized AgNPs were determined by using various physical techniques. The TEM analysis revealed the AgNPs less than 50 nm in size and spherical shaped. For antibacterial assays, different concentrations (1000–15.62 µg/mL, 2-fold dilutions) of the extract-free AgNPs (Ef-AgNPs) or extract-mixed AgNPs (Em-AgNPs), and fruit extracts (FE) were used against plant pathogenic bacteria Erwinia carotovora subsp. carotovora, Erwinia carotovora subsp. atroseptica, and Ralstonia solanacearum. In the in vitro assays, we found significant inhibition of both bacterial species in response to maximum concentrations of AgNPs. Overall, Ef-AgNPs exhibited a higher percent inhibition of bacterial pathogens. In potato tubers assay, complete inhibition of Erwinia carotovora was observed, except for the lowest AgNPs concentration of 15.62 µg/mL. Similarly, exposure of tomato plants to Ralstonia solanacearum suspensions (OD600 = 0.2) in the soil-drenching experiment and post-exposure treatment with 1000 µg/mL and 125 µg/mL of AgNPs resulted in disease inhibition. This study provides the basis that biogenic nanoparticles prepared from Hedera nepalensis are one of the best substitutes to synthetic pesticide, having displayed better results to control the growth of phytopathogenic microbes. However, field studies need to be conducted in a controlled environment to scale up the current work and find out the efficacy of nanoparticles on a larger scale. [ABSTRACT FROM AUTHOR]

The last decade's developments in sensor technologies and artificial intelligence applications have received extensive attention for daily life activity recognition. Autism spectrum disorder (ASD) in children is a neurological development disorder that causes significant impairments in social interaction, communication, and sensory action deficiency. Children with ASD have deficits in memory, emotion, cognition, and social skills. ASD affects children's communication skills and speaking abilities. ASD children have restricted interests and repetitive behavior. They can communicate in sign language but have difficulties communicating with others as not everyone knows sign language. This paper proposes a body-worn multi-sensor-based Internet of Things (IoT) platform using machine learning to recognize the complex sign language of speech-impaired children. Optimal sensor location is essential in extracting the features, as variations in placement result in an interpretation of recognition accuracy. We acquire the time-series data of sensors, extract various time-domain and frequency-domain features, and evaluate different classifiers for recognizing ASD children's gestures. We compare in terms of accuracy the decision tree (DT), random forest, artificial neural network (ANN), and k-nearest neighbour (KNN) classifiers to recognize ASD children's gestures, and the results showed more than 96% recognition accuracy. [ABSTRACT FROM AUTHOR]

Floods have caused major losses and damages to people, infrastructure, and the environment. This study aims to assess the risk perception of households prone to riverine and flash floods and the perceived damages to infrastructure and livelihoods. Data were collected from 382 households through a questionnaire survey and analyzed using chi-squared and t-tests. Overall, risk perception was higher for riverine floods. Similarly, 'flood coping capacities', 'livelihood disruption', 'change in lifestyle/adjusting to floods', and 'change in the relationship' were also high for riverine floods and statistically significant (p-value < 0.05). The 'likelihood of future flood damages' perception was higher for flash floods (mean values: 0.913 vs. 0.779), while the 'infrastructural damages' showed the same results. The perceptions of 'livelihoods' and perceived 'economic loss' were greater for riverine floods (p-value < 0.05). The perceptions of 'livestock damages' and 'household damages' were higher for flash floods. [ABSTRACT FROM AUTHOR]

Simple Summary: The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), is a voracious insect pest native to the Western Hemisphere, particularly in South America. The polyphagous fall armyworm feeds on more than 350 plants in such families, including Poaceae, Asteraceae, and Fabaceae. Transgenic plants that express Bacillus thuringiensis proteins (Bt plants) and synthetic insecticides are the main tactics to control Spodoptera frugiperda, although widespread usage of synthetic chemicals has resulted in the emergence of resistance. We assessed cross-resistance, resistance mechanism, and fitness costs based on the life history traits of Spodoptera frugiperda. Results indicated that after 24 generations of selection, the resistance to indoxacarb was increased by 472.67-fold as compared to the Ind-UNSEL. Significantly longer developmental time of larvae extended pupal duration, shorter adult longevity, and lower fecundity were observed in Ind-SEL as compared with the Ind-UNSEL population. Butoxide synergist increased susceptibility to indoxacarb, indicating that P450 enzymes may be involved in indoxacarb resistance. Therefore, it is crucial that we comprehend how insecticides work and how resistance develops in order to develop techniques for managing resistance. These data are valuable to understand the indoxacarb resistance mechanism and provides vital information for scientific-based guidance of pest management decisions. The fall armyworm, Spodoptera frugiperda (J.E. Smith), is a voracious insect pest that is difficult to control due to resistance to insecticides and Bt proteins. We assessed cross-resistance, resistance mechanism, and fitness costs based on the life history traits of S. frugiperda. We established an S. frugiperda strain selected for resistance to indoxacarb (Ind-SEL) from a field-collected population and an unselected strain, Ind-UNSEL. Results indicated that after 24 generations of selection, the resistance to indoxacarb was increased by 472.67-fold as compared to the Ind-UNSEL. There was high cross-resistance to deltamethrin (31.23-fold) with very low or negligible cross-resistance to chlorantraniliprole, emamectin benzoate, and/or methoxyfenozide in the Ind-SEL population. Butoxide synergist increased susceptibility to indoxacarb, indicating that P450 enzymes may be involved in indoxacarb resistance. Significantly longer developmental time of larvae extended pupal duration, shorter adult longevity, and lower fecundity were observed in Ind-SEL as compared with the Ind-UNSEL population. The Net reproductive rate (R0) was the only growth parameter that differs between crosses of Ind-SEL♂ × Ind-UNSEL♀ (176 ± 46) and Ind-SEL♀ × Ind-UNSEL♂ (328 ± 57). On the other hand, all population growth parameters differ between Ind-SEL and Ind-UNSEL strains. Our work contributes to the growing body of research that demonstrates the importance of strain genetics in fitness cost experiments and helps resistance management programs make decisions. [ABSTRACT FROM AUTHOR]

Imidacloprid is one of the most widely used neonicotinoid insecticides to control sap-sucking insect pests, including Aphis gossypii. The intensive application of chemical insecticides to A. gossypii led to the development of resistance against several insecticides, including imidacloprid. Therefore, it is crucial to understand the association between imidacloprid resistance and the fitness of A. gossypii to limit the spread of the resistant population under field contexts. In this study, we used the age-stage, two-sex life table method to comprehensively investigate the fitness of imidacloprid resistant (ImR) and susceptible strains (SS) of melon aphids. Results showed that ImR aphids have prolonged developmental stages and decreased longevity, fecundity, and reproductive days. The key demographic parameters (r, λ, and R0) were significantly reduced in ImR strain compared to SS aphids. Additionally, the molecular mechanism for fitness costs was investigated by comparing the expression profile of juvenile hormone-binding protein (JHBP), juvenile hormone epoxide hydrolase (JHEH), juvenile hormone acid O-methyltransferase (JHAMT), Vitellogenin (Vg), ecdysone receptor (EcR), and ultraspiracle protein (USP) supposed to be associated with development and reproduction in insects. The results of RT-qPCR showed that EcR, JHBP, JHAMT, JHEH, and Vg genes were downregulated, while USP was statistically the same in ImR A. gossypii compared to the SS strain. Together, these results provide in-depth information about the occurrence and magnitude of fitness costs against imidacloprid resistance that could help manage the evolution and spread of A. gossypii resistance in field populations [ABSTRACT FROM AUTHOR]

The fall armyworm of maize, Spodoptera frugiperda (J. E. Smith) (Lepidoptera; Noctuidae) is capable of causing a 100% yield loss due to its unforeseen occurrence from the seedling to the cob formation stage. To manage this serious pest, maize growers are tending to apply a high dosage of pesticides. This indiscriminate usage of pesticides has resulted in an unacceptable amount of insect resurgence in maize, harming maize production and consumption. In this review, we prepared a list of practical pest management options, including host plant resistance, agronomical, cultural, biological, botanical, chemical, and biotechnology approaches. It was found that cultivation of tolerant genotypes, adjusting sowing windows, and practicing specific intercultural and cropping systems measures in addition to chemical and non-chemical pest management strategies showed encouraging results for sustainable management of fall armyworm, which could protect the crop. This review highlights novel and successful management options advocated in various parts of the world. Recommendations documented in this paper would certainly pave the way for successful management of fall armyworm in maize and other concerned crops. [ABSTRACT FROM AUTHOR]

We confined the formation and characterization of heterogenous nano-catalysts and then used them to produce biodiesel from the novel non-edible seed oil of Prunus aitchisonii. P. aitchisonii seeds' oil content was extracted at about 52.4 ± 3% with 0.77% FFA. Three different heterogenous nano-catalysts—calcined (CPC), KPC, and KOH-activated P. aitchisonii cake Titanium Dioxide (TiO2)—were synthesized using calcination and precipitation methods. The mentioned catalysts were characterized through XRD, SEM, and EDX to inspect their crystallin dimension, shape, and arrangement. Titanium dioxide has morphological dimensions so that the average particle size ranges from 49–60 nm. The result shows that the crystal structure of TiO2 is tetragonal (Anatase). The surface morphology of CPC illustrated that the roughness of the surface was increased after calcination, many macropores and hollow cavities appeared, and the external structure became very porous. These changes in morphology may increase the catalytic efficiency of CPC than non-calcined Prunus aitchisonii oil cake. The fuel belonging to PAOB stood according to the series suggested by ASTM criteria. All the characterization reports that P. aitchisonii is a novel and efficient potential source of biodiesel as a green energy source. [ABSTRACT FROM AUTHOR]

Hormesis for the intractable pests can be dreadful, but for natural enemies of pests, it is a puissant strategy in optimizing their mass rearing. We report multigenerational stimulatory effects of widely used insecticide, imidacloprid, on the demographic traits of an important egg parasitoid Trichogramma chilonis Ishii. The study investigated the consequences of sublethal (LC5), low lethal (LC30), and median lethal (LC50) concentrations, as well as a control, for five continuous generations (F1 to F5). The initial bioassay experiments revealed imidacloprid exhibiting the highest toxicity for the parasitoid with a LC50 of 2 µg·L−1, whereas LC5 and LC30 were 0.07 µg·L−1 and 0.6 µg·L−1, respectively. Among biological traits, compared to the F1 individuals, a substantial increase in the fecundity of T. chilonis was observed in the F5 individuals by 54.92% and 46.81% when exposed to LC5 and LC30, respectively (p < 0.00001). Further, there was a significant enhancement in the adult longevity as well as oviposition days of the F5 individuals at both these concentrations. Considering the population traits, along with gross reproductive rate (GRR), net reproductive rate (R0) was also enhanced by both LC5 and LC30 in F5 individuals than F1; whereas the intrinsic rate of increase (r) and finite rate of increase (λ) were enhanced only at LC30 upon comparing with control. On the other hand, LC50 exposure to T. chilonis did not result in notable differences in biological or population traits when compared across generations (F1 and F5). Low and sublethal concentrations of imidacloprid did not have a major influence on demographic traits of T. chilonis at initial generations of exposure but can induce hormetic effects in the subsequent generations. Overall, imidacloprid-induced hormesis stimulating the development of T. chilonis might be helpful under circumstances of mild exposure of imidacloprid in fields and could be leveraged for its mass rearing. [ABSTRACT FROM AUTHOR]

Foodborne diseases are one of the major causes of morbidity and mortality, especially in low-income countries with poor sanitation and inadequate healthcare facilities. The foremost bacterial pathogens responsible for global outbreaks include Salmonella species, Campylobacter jejuni, Escherichia coli, Shigella sp., Vibrio, Listeria monocytogenes and Clostridium botulinum. Among the viral and parasitic pathogens, norovirus, hepatitis A virus, Giardia lamblia, Trichinella spiralis, Toxoplasma and Entamoeba histolytica are commonly associated with foodborne diseases. The toxins produced by Staphylococcus aureus, Bacillus cereus and Clostridium perfringens also cause these infections. The currently available therapies for these infections are associated with various limited efficacy, high cost and side-effects. There is an urgent need for effective alternative therapies for the prevention and treatment of foodborne diseases. Several plant extracts and phytochemicals were found to be highly effective to control the growth of these pathogens causing foodborne infections in in vitro systems. The present review attempts to provide comprehensive scientific information on major foodborne pathogens and the potential role of phytochemicals in the prevention and treatment of these infections. Further detailed studies are necessary to evaluate the activities of these extracts and phytochemicals along with their mechanism of action using in vivo models. [ABSTRACT FROM AUTHOR]

In post-disaster scenarios, such as after floods, earthquakes, and in war zones, the cellular communication infrastructure may be destroyed or seriously disrupted. In such emergency scenarios, it becomes very important for first aid responders to communicate with other rescue teams in order to provide feedback to both the central office and the disaster survivors. To address this issue, rapidly deployable systems are required to re-establish connectivity and assist users and first responders in the region of incident. In this work, we describe the design, implementation, and evaluation of a rapidly deployable system for first response applications in post-disaster situations, named RDSP. The proposed system helps early rescue responders and victims by sharing their location information to remotely located servers by utilizing a novel routing scheme. This novel routing scheme consists of the Dynamic ID Assignment (DIA) algorithm and the Minimum Maximum Neighbor (MMN) algorithm. The DIA algorithm is used by relay devices to dynamically select their IDs on the basis of all the available IDs of networks. Whereas, the MMN algorithm is used by the client and relay devices to dynamically select their next neighbor relays for the transmission of messages. The RDSP contains three devices; the client device sends the victim’s location information to the server, the relay device relays information between client and server device, the server device receives messages from the client device to alert the rescue team. We deployed and evaluated our system in the outdoor environment of the university campus. The experimental results show that the RDSP system reduces the message delivery delay and improves the message delivery ratio with lower communication overhead. [ABSTRACT FROM AUTHOR]

Our understanding of the post-transcriptional mechanisms involved in follicular atresia is limited; however, an important development has been made in understanding the biological regulatory networks responsible for mediating follicular atresia. MicroRNAs have come to be seen as a key regulatory actor in determining cell fate in a wide range of tissues in normal and pathological processes. Profiling studies of miRNAs during follicular atresia and development have identified several putative miRNAs enriched in apoptosis signaling pathways. Subsequent in vitro and/or in vivo studies of granulosa cells have elucidated the functional role of some miRNAs along with their molecular pathways. In particular, the regulatory roles of some miRNAs have been consistently observed during studies of follicular cellular apoptosis. Continued work should gradually lead to better understanding of the role of miRNAs in this field. Ultimately, we expect this understanding will have substantial benefits for fertility management at both the in vivo or/and in vitro levels. The stable nature of miRNA holds remarkable promise in clinical use as a diagnostic tool and in reproductive medicine to solve the ever-increasing fertility problem. In this review, we summarize current knowledge of the involvement of miRNAs in follicular atresia, discuss the challenges for further work and pinpoint areas for future research. [ABSTRACT FROM AUTHOR]

User interactions in online social networks (OSNs) enable the spread of information and enhance the information dissemination process, but at the same time they exacerbate the information overload problem. In this paper, we propose a social content recommendation method based on spatial-temporal aware controlled information diffusion modeling in OSNs. Users interact more frequently when they are close to each other geographically, have similar behaviors, and fall into similar demographic categories. Considering these facts, we propose multicriteria-based social ties relationship and temporal-aware probabilistic information diffusion modeling for controlled information spread maximization in OSNs. The proposed social ties relationship modeling takes into account user spatial information, content trust, opinion similarity, and demographics. We suggest a ranking algorithm that considers the user ties strength with friends and friends-of-friends to rank users in OSNs and select highly influential injection nodes. These nodes are able to improve social content recommendations, minimize information diffusion time, and maximize information spread. Furthermore, the proposed temporal-aware probabilistic diffusion process categorizes the nodes and diffuses the recommended content to only those users who are highly influential and can enhance information dissemination. The experimental results show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Rickettsia spp. associated with ticks infesting wild animals have been mostly neglected in several countries, including Pakistan. To address this knowledge gap, ticks were collected during 2017 to 2021 from wild animals including cats (Felis chaus), Indian hedgehogs (Paraechinus micropus), and wild boars (Sus scrofa). The collected ticks were morpho-molecularly identified and screened for the detection of Rickettsia spp. Morphologically identified ticks were categorized into four species of the genus Rhipicephalus: Rhipicephalus haemaphysaloides, Rh. turanicus, Rh. sanguineus sensu lato (s.l), and Rh. microplus. Among 53 wild animals examined, 31 were infested by 531 ticks, an overall prevalence of 58.4%. Adult female ticks were predominant (242 out of 513 ticks collected, corresponding to 46%) in comparison with males (172, 32%), nymphs (80, 15%) and larvae (37, 7%). The most prevalent tick species was Rh. turanicus (266, 50%), followed by Rh. microplus (123, 23%), Rh. sanguineus (106, 20%), and Rh. haemaphysaloides (36, 7%). Among the screened wild animals, wild boars were the most highly infested, with 268 ticks being collected from these animals (50.4%), followed by cats (145, 27.3%) and hedgehogs (118, 22.3%). Tick species Rh. haemaphysaloides, Rh. turanicus, and Rh. sanguineus were found on wild boars, Rh. haemaphysaloides, and Rh. microplus on cats, and Rh. turanicus on hedgehogs. In a phylogenetic analysis, mitochondrial cytochrome C oxidase 1 (cox1) sequences obtained from a subsample (120) of the collected ticks clustered with sequences from Bangladesh, China, India, Iran, Myanmar, and Pakistan, while 16S ribosomal DNA (16S rDNA) sequences clustered with sequences reported from Afghanistan, Egypt, India, Pakistan, Romania, Serbia, and Taiwan. Among Rickettsia infected ticks (10/120, 8.3%), Rh. turanicus (7/10, 70%), and Rh. haemaphysaloides (3/10, 30%) were found infesting wild boars in the districts Mardan and Charsadda. The obtained rickettsial gltA gene sequences showed 99% and ompA gene sequences showed 100% identity with Rickettsia massiliae, and the phylogenetic tree shows ompA clustered with the same species reported from France, Greece, Spain, and USA. This study emphasizes the need for effective surveillance and control programs in the region to prevent health risks due to tick-borne pathogens, and that healthy infested wild animals may play a role in the spread of these parasites. [ABSTRACT FROM AUTHOR]

How herbivorous insects adapt to host plants is a key question in ecological and evolutionary biology. The fall armyworm, (FAW) Spodoptera frugiperda (J.E. Smith), although polyphagous and a major pest on various crops, has been reported to have a rice and corn (maize) feeding strain in its native range in the Americas. The species is highly invasive and has recently established in China. We compared behavioral changes in larvae and adults of a corn population (Corn) when selected on rice (Rice) and the molecular basis of these adaptational changes in midgut and antennae based on a comparative transcriptome analysis. Larvae of S. frugiperda reared on rice plants continuously for 20 generations exhibited strong feeding preference for with higher larval performance and pupal weight on rice than on maize plants. Similarly, females from the rice selected population laid significantly more eggs on rice as compared to females from maize population. The most highly expressed DEGs were shown in the midgut of Rice vs. Corn. A total of 6430 DEGs were identified between the populations mostly in genes related to digestion and detoxification. These results suggest that potential adaptations for feeding on rice crops, may contribute to the current rapid spread of fall armyworm on rice crops in China and potentially elsewhere. Consistently, highly expressed DEGs were also shown in antennae; a total of 5125 differentially expressed genes (DEGs) s were identified related to the expansions of major chemosensory genes family in Rice compared to the Corn feeding population. These results not only provide valuable insight into the molecular mechanisms in host plants adaptation of S. frugiperda but may provide new gene targets for the management of this pest. [ABSTRACT FROM AUTHOR]

Granulosa cells (GCs) are essential for follicular growth, development, and atresia. The orexin-A (OXA) neuropeptide is widely involved in the regulation of various biological functions. OXA selectively binds to orexin receptor type 1 (OX1R) and mediates all its biological actions via OX1R. This study aimed to explore the expression of OXA and OX1R and their regulatory role in GCs proliferation, cell cycle progression, apoptosis, oocyte maturation, and underlying molecular mechanisms of these processes and elucidate its novel signaling pathway. Western blotting and RT-qPCR showed that OXA and OX1R were expressed during different developmental stages of GCs, and siRNA transfection successfully inhibited the expression of OX1R at the translational and transcriptional levels. Flow cytometry revealed that OX1R knockdown upregulated GCs apoptosis and triggered S-phase arrest in cell cycle progression. RT-qPCR and Western blotting showed significantly reduced expression of Bcl-2 and elevated expression of Bax, caspase-3, TNF-α, and P21 in OX1R-silenced GCs. Furthermore, the CCK-8 assay showed that knockdown of OX1R suppressed GCs proliferation by downregulating the expression of PCNA, a proliferation marker gene, at the translational and transcriptional levels. Western blotting revealed that knockdown of OX1R resulted in a considerable decrease of the phosphorylation level of the AKT and ERK1/2 proteins, indicating that the AKT/ERK1/2 pathway is involved in regulating GCs proliferation and apoptosis. In addition, OX1R silencing enhanced the mRNA expression of GDF9 and suppressed the mRNA expression of BMP15 in mouse GCs. Collectively, these results reveal a novel regulatory role of OXA in the development of GCs and folliculogenesis by regulating proliferation, apoptosis, and cell cycle progression. Therefore, OXA can be a promising therapeutic agent for female infertility. [ABSTRACT FROM AUTHOR]

The epidemic disease of Severe Acute Respiratory Syndrome (SARS) called COVID-19 has become a more frequently active disease. Managing and monitoring COVID-19 patients is still a challenging issue for advanced technologies. The first and foremost critical issue in COVID-19 is to diagnose it timely and cut off the chain of transmission by isolating the susceptible and patients. COVID-19 spreads through close interaction and contact with an infected person. It has affected the entire world, and every country is facing the challenges of having adequate medical facilities along with the availability of medical staff in rural and urban areas that have a high number of patients due to the pandemic. Due to the invasive method of treatment, SARS-COVID is spreading swiftly. In this paper, we propose an intelligent health monitoring framework using wearable Internet of Things (IoT) and Geo-fencing for COVID-19 susceptible and patient monitoring, and isolation and quarantine management to control the pandemic. The proposed system consists of four layers, and each layer has different functionality: a wearable sensors layer, IoT gateway layer, cloud server layer, and client application layer for visualization and analysis. The wearable sensors layer consists of wearable biomedical and GPS sensors for physiological parameters, and GPS and Wi-Fi Received Signal Strength Indicator acquisition for health monitoring and user Geo-fencing. The IoT gateway layer provides a Bluetooth and Wi-Fi based wireless body area network and IoT environment for data transmission anytime and anywhere. Cloud servers use Raspberry Pi and ThingSpeak cloud for data analysis and web-based application layers for remote monitoring based on user consent. The susceptible and patient conditions, real-time sensor's data, and Geo-fencing enables minimizing the spread through close interaction. The results show the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

We propose a physical activity recognition and monitoring framework based on wearable sensors during maternity. A physical activity can either create or prevent health issues during a given stage of pregnancy depending on its intensity. Thus, it becomes very important to provide continuous feedback by recognizing a physical activity and its intensity. However, such continuous monitoring is very challenging during the whole period of maternity. In addition, maintaining a record of each physical activity, and the time for which it was performed, is also a non-trivial task. We aim at such problems by first recognizing a physical activity via the data of wearable sensors that are put on various parts of body. We avoid the use of smartphones for such task due to the inconvenience caused by wearing it for activities such as "eating". In our proposed framework, a module worn on body consists of three sensors: a 3-axis accelerometer, 3-axis gyroscope, and temperature sensor. The time-series data from these sensors are sent to a Raspberry-PI via Bluetooth Low Energy (BLE). Various statistical measures (features) of this data are then calculated and represented in features vectors. These feature vectors are then used to train a supervised machine learning algorithm called classifier for the recognition of physical activity from the sensors data. Based on such recognition, the proposed framework sends a message to the care-taker in case of unfavorable situation. We evaluated a number of well-known classifiers on various features developed from overlapped and non-overlapped window size of time-series data. Our novel dataset consists of 10 physical activities performed by 61 subjects at various stages of maternity. On the current dataset, we achieve the highest recognition rate of 89% which is encouraging for a monitoring and feedback system. [ABSTRACT FROM AUTHOR]

Autistic people face many challenges in various aspects of daily life such as social skills, repetitive behaviors, speech, and verbal communication. They feel hesitant to talk with others. The signs of autism vary from one individual to another, with a range from mild to severe. Autistic children use fewer communicative gestures compared with typically developing children (TD). With time, the parents may learn their gestures and understand what is occurring in their child's mind. However, it is difficult for other people to understand their gestures. In this paper, we propose a wearable-sensors-based platform to recognize autistic gestures using various classification techniques. The proposed system defines, monitors, and classifies the gestures of the individuals. We propose using wearable sensors that transmit their data using a Bluetooth interface to a data acquisition and classification server. A dataset of 24 gestures is created by 10 autistic children performing each gesture about 10 times. Time- and frequency-domain features are extracted from the sensors' data, which are classified using k-nearest neighbor (KNN), decision tree, neural network, and random forest models. The main objective of this work is to develop a wearable-sensor-based IoT platform for gesture recognition in children with autism spectrum disorder (ASD). We achieve an accuracy of about 91% with most of the classifiers using dataset cross-validation and leave-one-person-out cross-validation. [ABSTRACT FROM AUTHOR]

The professional sports events industry is becoming immensely popular due to a global social shift toward larger numbers of spectators at sports events and an ever-increasing variety of such events. This study aimed to investigate the impact of spectators' perception of corporate social responsibility on regional attachment by applying social identity theory. The present study introduces two mediators, namely, spectators' pride and team identification, to enlighten the relationship between spectators' perception of corporate social responsibility and regional attachment, thus contributing to the literature on corporate social responsibility in sports. This quantitative study used a time-lagged approach to collect data in three waves at a time interval of one week and the final sample consisted of 511 respondents (i.e., spectators). Hierarchical regression analysis bootstrapping approach was utilized to analyze the hypothesis. We found that the spectators' perceptions of corporate social responsibility positively influenced their team identification, and this relationship was mediated by spectators' pride. In addition, spectators' pride positively influences regional attachment, and this relationship is mediated by team identification. These findings provide new directions for understanding corporate social responsibility, team identification, spectators' pride, and regional attachment in sports contexts. The practical and theoretical implications are discussed. [ABSTRACT FROM AUTHOR]

Cloud computing use is exponentially increasing with the advent of industrial revolution 4.0 technologies such as the Internet of Things, artificial intelligence, and digital transformations. These technologies require cloud data centers to process massive volumes of workloads. As a result, the data centers consume gigantic amounts of electrical energy, and a large portion of data center electrical energy comes from fossil fuels. It causes greenhouse gas emissions and thus ensuing in global warming. An adaptive resource utilization mechanism of cloud data center resources is vital to get by with this huge problem. The adaptive system will estimate the resource utilization and then adjust the resources accordingly. Cloud resource utilization estimation is a two-fold challenging task. First, the cloud workloads are sundry, and second, clients' requests are uneven. In the literature, several machine learning models have estimated cloud resources, of which artificial neural networks (ANNs) have shown better performance. Conventional ANNs have a fixed topology and allow only to train their weights either by back-propagation or neuroevolution such as a genetic algorithm. In this paper, we propose Cartesian genetic programming (CGP) neural network (CGPNN). The CGPNN enhances the performance of conventional ANN by allowing training of both its parameters and topology, and it uses a built-in sliding window. We have trained CGPNN with parallel neuroevolution that searches for global optimum through numerous directions. The resource utilization traces of the Bitbrains data center is used for validation of the proposed CGPNN and compared results with machine learning models from the literature on the same data set. The proposed method has outstripped the machine learning models from the literature and resulted in 97% prediction accuracy. [ABSTRACT FROM AUTHOR]

Optimal Reactive Power Dispatch (ORPD) is the vital concern of network operators in the planning and management of electrical systems to reduce the real and reactive losses of the transmission and distribution system in order to augment the overall efficiency of the electrical network. The principle objective of the ORPD problem is to explore the best setting of decision variables such as rating of the shunt capacitors, output voltage of the generators and tap setting of the transformers in order to diminish the line loss, and improve the voltage profile index (VPI) and operating cost minimization of standard electrical systems while keeping the variables within the allowable limits. This research study demonstrates a compelling transformative approach for resolving ORPD problems faced by the operators through exploiting the strength of the meta-heuristic optimization model based on a new fractional swarming strategy, namely fractional order (FO)–particle swarm optimization (PSO), with consideration of the entropy metric in the velocity update mechanism. To perceive ORPD for standard 30 and 57-bus networks, the complex nonlinear objective functions, including minimization of the system, VPI improvement and operating cost minimization, are constructed with emphasis on efficacy enhancement of the overall electrical system. Assessment of the results show that the proposed FO-PSO with entropy metric performs better than the other state of the art algorithms by means of improvement in VPI, operating cost and line loss minimization. The statistical outcomes in terms of quantile–quantile illustrations, probability plots, cumulative distribution function, box plots, histograms and minimum fitness evaluation in a set of autonomous trials validate the capability of the proposed optimization scheme and exhibit sufficiency and also vigor in resolving ORPD problems. [ABSTRACT FROM AUTHOR]

Wireless Body Area Networks (WBANs) and Wireless Local Area Networks (WLANs) have been widely regarded as solution providers for future Cyber-Physical Systems (CPS)-based ehealthcare amenities. The IEEE 802.11 standard specifies media access protocols in wireless networks, along with channel access methods. WBANs are expected to improve the existing healthcare services significantly, but several research challenges also have to be tackled for apt utilization of the technology. Guarantee of Quality-of-Service (QoS) differentiation between various health parameters, such as temperature and blood pressure, during mobility is a major challenge for the provision of ehealthcare services. The scheme proposed in this paper for the Mobile Wi-Fi based connectivity of WBANs is designed to provide QoS-based priorities for ehealthcare subscribers by altering the Contention Window (CW) for different applications of patient health monitoring. The relationship between CW and QoS is utilized to achieve efficient resource assignment. Three different health parameters, i.e., ECG (Electrocardiogram), BP (blood pressure) and temperature. are monitored using medical CPS in this work. The performance evaluation results, such as end-to-end packet delay and throughput for various data traffic classes reveal that the proposed scheme improves QoS provision. [ABSTRACT FROM AUTHOR]

Chitin is a vital part of the insect exoskeleton and peritrophic membrane, synthesized by chitin synthase (CHS) enzymes. Chitin synthase 1 (CHS1) is a crucial enzyme in the final step of chitin biosynthetic pathway and consequently plays essential role towards insect growth and molting. RNA interference (RNAi) is an agent that could be used as an extremely target-specific and ecologically innocuous tactic to control different insect pests associated with economically important crops. The sole purpose of the current study is to use CHS1 as the key target gene against the cotton-melon aphid, Aphis gossypii, via oral feeding on artificial diets mixed with dsRNA-CHS1. Results revealed that the expression level of CHS1 gene significantly decreased after the oral delivery of dsRNA-CHS1. The knockdown of CHS1 gene caused up to 43%, 47%, and 59% mortality in third-instar nymph after feeding of dsCHS1 for 24, 48, and 72 h, respectively, as compared to the control. Consistent with this, significantly lower longevity (approximately 38%) and fecundity (approximately 48%) were also found in adult stage of cotton-melon aphids that were fed with dsCHS1 for 72 h at nymphal stage. The qRT-PCR analysis of gene expression demonstrated that the increased mortality rates and lowered longevity and fecundity of A. gossypii were attributed to the downregulation of CHS1 gene via oral-delivery-mediated RNAi. The results of current study confirm that CHS1 could be an appropriate candidate target gene for the RNAi-based control of cotton-melon aphids. [ABSTRACT FROM AUTHOR]

Simple Summary: Anaerobic rumen fungi play a vital role in fiber degradation. The objective of this study was to compare the anaerobic rumen fungal communities of full grazing ruminants in the Qinghai-Tibetan Plateau. Our results showed that the anaerobic rumen fungal community was affected by host species and the dynamic associations of them were host specific. This is the first study exploring the anaerobic rumen fungi in the full-grazing ruminants, which could lay a solid foundation to really identify fiber degradation fungal taxa using culture-dependent techniques in the future. The anaerobic rumen fungal community play a critical role in fibrous material degradation. However, there is a lack of data describing the composition of anaerobic rumen fungal community of full grazing ruminants in the Qinghai-Tibetan Plateau. For this reason, we employed the next-generation sequencing technique to elucidate the rumen fungal structure composition and evaluate the effects of host species on fungal communities. Community comparisons (Bray–Curtis index) between yak and Tibetan sheep revealed that the rumen fungal community was affected by host species (p < 0.05). The alpha diversity indices in the yak were significantly higher than in the Tibetan sheep and Small Tail Han sheep. Neocallimastigomycota was predominant regardless of host species. Within this phylum, unidentified genus of Neocallimastigaceae was the most dominant in all samples, followed by Piromyces and Orpinomyces. Moreover, the shared and unique OTUs in the rumen were identified and most of them belonged to the Orpinomyces. Co-occurrence network analysis identified that each animal species had their own keystone species and most of them were non-dominant flora. Our data indicate that host breeds override living environment as the key factor that determines fungal community in the rumen of grazing ruminants in the Qinghai-Tibetan Plateau. [ABSTRACT FROM AUTHOR]

We perform image-based denomination recognition of the Pakistani currency notes. There are a total of seven different denominations in the current series of Pakistani notes. Apart from color and texture, these notes differ from one another mainly due to their aspect ratios. Our aim is to exploit this single feature to attain an image-based recognition that is invariant to the most common image variations found in currency notes images. Among others, the most notable image variations are caused by the difference in positions and in-plane orientations of the currency notes in images. While most of the proposed methods for currency denomination recognition only focus on attaining higher recognition rates, our aim is more complex, i.e., attaining a high recognition rate in the presence of image variations. Since, the aspect ratio of a currency note is invariant to such differences, an image-based recognition of currency notes based on aspect ratio is more likely to be translation- and rotation-invariant. Therefore, we adapt a two step procedure that first extracts a currency note from the homogeneous image background via local entropy and range filters. Then, the aspect ratio of the extracted currency note is calculated to determine its denomination. To validate our proposed method, we gathered a new dataset with the largest and most diverse collection of Pakistani currency notes, where each image contains either a single or multiple notes at arbitrary positions and orientations. We attain an overall average recognition rate of 99% which is very encouraging for our method, which relies on a single feature and is suited for real-time applications. Consequently, the method may be extended to other international and historical currencies, which makes it suitable for business and digital humanities applications. [ABSTRACT FROM AUTHOR]

The paper proposes a sensors platform to control a barrier that is installed for vehicles entrance. This platform is automatized by image-based license plate recognition of the vehicle. However, in situations where standardized license plates are not used, such image-based recognition becomes non-trivial and challenging due to the variations in license plate background, fonts and deformations. The proposed method first detects the approaching vehicle via ultrasonic sensors and, at the same time, captures its image via a camera installed along with the barrier. From this image, the license plate is automatically extracted and further processed to segment the license plate characters. Finally, these characters are recognized with the help of a standard optical character recognition (OCR) pipeline. The evaluation of the proposed system shows an accuracy of 98% for license plates extraction, 96% for character segmentation and 93% for character recognition. [ABSTRACT FROM AUTHOR]

This study aimed to appraise the anti-leishmanial potentials of benzoic acid derivatives, including methyl 3,4-dihydroxybenzoate (compound 1) and octadecyl benzoate (compound 2), isolated from the ethnomedicinally important plant Ifloga spicata (I. spicata). Chemical structures were elucidated via FT-IR, mass spectrometry, and multinuclear (1H and 13C) NMR spectroscopy. Anti-leishmanial potentials of the compounds were assessed using Leishmania tropica promastigotes. Moreover, acridine orange fluorescent staining was performed to visualize the apoptosis-associated changes in promastigotes under a fluorescent microscope. A SYTOX assay was used to check rupturing of Leishmania promastigote cell membranes using 0.1% Triton X-100 as positive control. A DNA interaction assay was carried out to assess DNA attachment potential. AutoDock software was used to check the binding affinity of compounds with surface enzyme leishmanolysin gp63 (1LML). Both compounds exhibited considerable anti-leishmanial potential, with LD50 values of 10.40 ± 0.09 and 14.11 ± 0.11 μg/mL for compound 1 and compound 2, respectively. Both compounds showed higher binding affinity with the leishmanolysin (gp63) receptor/protease of Leishmania, as assessed using computational analysis. The binding scores of compounds 1 and 2 with target gp63 were −5.3 and −5.6, respectively. The attachment of compounds with this receptor resulted in their entry into the cell where they bound with Leishmania DNA, causing apoptosis. The results confirmed that the investigated compounds have anti-leishmanial potential and are potential substitutes as natural anti-leishmanial agents against L. tropica. [ABSTRACT FROM AUTHOR]

A novel varactor circuit exhibiting a wider tuning range and a new technique for quadrature coupling of LC-Voltage Controlled Oscillator (LC-VCO) is presented and validated on a 25 GHz oscillator. The proposed varactor circuit employs distribute-biased parallel varactors with a series inductor connected at both ends of the varactor bank to extend the tuning range of the oscillator. Similarly, the quadrature coupling is accomplished by employing the 2nd harmonic, explicitly generated in the stand-alone free-running differential oscillator using frequency doubler. As an example, the Differential VCO (DVCO) is tunable between 20 GHz and 31 GHz and exhibits the best Phase Noise (P N) of −100 dBc/Hz at 1 MHz offset frequency. Similarly, the Quadrature VCO (QVCO) covers 42% tuning bandwidth around 25 GHz oscillation frequency, which is significantly wider than other state-of-the-art VCOs at comparable frequencies. In addition, all the oscillators are designed in class-C to further improve their performances both in term of low power and low phase noise. The presented oscillators are designed using high-performance SiGe HBTs of the GlobalFoundries (GFs) 130 nm SiGe BiCMOS 8HP process. The presented DVCO and QVCO draw currents of approximately 10 mA and 21 mA, respectively from a 1.2 V supply. [ABSTRACT FROM AUTHOR]

This paper presents the design and measuring of a 6-bit SiGe BiCMOS digital step attenuator, with a maximum attenuation of 31.5 dB, and with 0.5 dB steps (64 states) that have the lowest RMS amplitude error and a low phase variation. To alleviate the large phase variation of the conventional attenuator at a higher frequency, the proposed attenuator utilizes a phase compensation circuit. The phase compensation circuit consists of a 2nd order low pass phase correction network, stacked in parallel to the switched π/T structure of each attenuation module. An attenuator with a phase compensation network shows a root mean square (RMS) amplitude error less than 0.43 dB, and the RMS insertion phase deviation varying from 1.6° to 4.2° over 20–24 GHz. The measured insertion loss is 21.9 dB and the input P1dB is 14.03 dBm at 22 GHz. Our confidence regarding the obtained results stems from a comparison of simulations, carried out using Cadence Virtuoso, and physical measurements using a network analyzer (also presented). The proposed attenuator’s design has a 0.13 μm SiGe BiCMOS process, with an approximate occupied area of 1.92 × 0.4 mm2 including chip pads. [ABSTRACT FROM AUTHOR]

In post-disaster scenarios, such as after floods, earthquakes, and in war zones, the cellular communication infrastructure may be destroyed or seriously disrupted. In such emergency scenarios, it becomes very important for first aid responders to communicate with other rescue teams in order to provide feedback to both the central office and the disaster survivors. To address this issue, rapidly deployable systems are required to re-establish connectivity and assist users and first responders in the region of incident. In this work, we describe the design, implementation, and evaluation of a rapidly deployable system for first response applications in post-disaster situations, named RDSP. The proposed system helps early rescue responders and victims by sharing their location information to remotely located servers by utilizing a novel routing scheme. This novel routing scheme consists of the Dynamic ID Assignment (DIA) algorithm and the Minimum Maximum Neighbor (MMN) algorithm. The DIA algorithm is used by relay devices to dynamically select their IDs on the basis of all the available IDs of networks. Whereas, the MMN algorithm is used by the client and relay devices to dynamically select their next neighbor relays for the transmission of messages. The RDSP contains three devices; the client device sends the victim's location information to the server, the relay device relays information between client and server device, the server device receives messages from the client device to alert the rescue team. We deployed and evaluated our system in the outdoor environment of the university campus. The experimental results show that the RDSP system reduces the message delivery delay and improves the message delivery ratio with lower communication overhead.

Personally identifiable information (PII) affects individual privacy because PII combinations may yield unique identifications in published data. User PII such as age, race, gender, and zip code contain private information that may assist an adversary in determining the user to whom such information relates. Each item of user PII reveals identity differently, and some types of PII are highly identity vulnerable. More vulnerable types of PII enable unique identification more easily, and their presence in published data increases privacy risks. Existing privacy models treat all types of PII equally from an identity revelation point of view, and they mainly focus on hiding user PII in a crowd of other users. Ignoring the identity vulnerability of each type of PII during anonymization is not an effective method of protecting user privacy in a fine-grained manner. This paper proposes a new anonymization scheme that considers the identity vulnerability of PII to effectively protect user privacy. Data generalization is performed adaptively based on the identity vulnerability of PII as well as diversity to anonymize data. This adaptive generalization effectively enables anonymous data, which protects user identity and private information disclosures while maximizing the utility of data for performing analyses and building classification models. Additionally, the proposed scheme has low computational overheads. The simulation results show the effectiveness of the scheme and verify the aforementioned claims.